research_review

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full responsibility for disclosing behavior. It reveals a key constraint (creators cannot self-accept; acceptance needs evidence) but does not state whether the tool mutates state, requires specific permissions, or what side effects occur. This leaves critical behavioral traits undisclosed for a review action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no redundant wording. The first sentence states the primary action, and the second adds a valuable constraint. It is concise and front-loaded, though the first sentence could have been more specific without losing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 5 parameters, an output schema, and is part of a family of research tools with distinct workflow roles. The minimal description does not explain how this review fits into the lifecycle, what the parameters mean, or what the output schema represents, leaving significant gaps for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate by explaining the 5 parameters. It only implicitly touches on actor and verdict via the self-accept rule, but record_id, comment, and expected_revision are not explained. The description fails to add meaning beyond the raw schema for most parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action ('Apply lifecycle review') and a resource (review), and adds a specific rule about self-acceptance and evidence. However, it does not explicitly distinguish from sibling tools like research_validate, and 'lifecycle review' is somewhat jargon-heavy without further context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives such as research_validate or research_propose. The rule about creators and evidence is a policy constraint, not a usage direction, and there is no mention of when not to use the tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.